Improved Model for Indoor Propagation Loss in the 5G FR2 Frequency Band

Abstract

One of the latest developments today is the 5G, or 5th generation mobile network. In addition to a number of innovations, the new system also includes millimeter-wavelength frequency ranges denoted with FR2, that formerly not applied for these specific purposes. Proper management of the transmitter and receiver antenna beams is required for efficient communication in this frequency range. For future use, the simplest implementation way is electronically shaping the antenna beams by an algorithm to orient the antennas in the best possible direction. The prerequisites for these algorithms are appropriate propagation models, which are currently lacking, and those that publicly available are not accurate enough for practical use.

Supporting Adaptive Coding and Modulation Techniques for Satellite Radio Channel

“…The idea is simple: the most significant influencing factor, fading, is categorised. The algorithm estimates the expected fading, and the ModCod settings can be adjusted accordingly [26]. For this purpose, supervised machine learning should be used, which requires the input data to be labelled [17].…”

“…However, there is currently no procedure or algorithm to do this, so the process is done manually. Therefore, the primary tests were carried out for a simplified case, binary classification [26]. In the binary case of fading labeling, we considered a local, drastic signal level drop as a fadig.…”

“…According to the previous statements, only the signal level to be taken, and Fig. 4: Binary fading prediction structure, part [26]. its function transformers, were calibrated; with a DNN that has memory.…”

Deep-Learning-Based Antenna Alignment Prediction for Mobile Indoor Communication

“…A schematic diagram of the procedure is shown in Figure 2 . It is known from previous research relating to indoor propagation that, based on these measurements, at a given frequency, it is possible to fit a model that well indicates the signal-receiving conditions [ 17 ]. If we know the direction of the next highest available signal level or if we can obtain this information with some post-processing, we can perform beam alignment with an algorithm based on these data.…”

“…As far as the outputs are concerned, estimating fewer categories is basically more accessible. However, on the basis of the results so far, 18 direction categories can be estimated with reasonable accuracy, each covering an area roughly equal to the beamwidth of the applied antenna [ 17 ]. The use of the fewest possible directions is also of particular importance since, in practice, it is likely that the same antenna will be used for each measurement.…”